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多模态移动性评估可预测小脑共济失调的跌倒频率和严重程度。

Multimodal Mobility Assessment Predicts Fall Frequency and Severity in Cerebellar Ataxia.

作者信息

Schniepp Roman, Huppert Anna, Decker Julian, Schenkel Fabian, Dieterich Marianne, Brandt Thomas, Wuehr Max

机构信息

Department of Neurology, University of Munich, Marchioninistrasse 15, 81377, Munich, Germany.

German Center for Vertigo and Balance Disorders (DSGZ), University of Munich, 81377, Munich, Germany.

出版信息

Cerebellum. 2023 Feb;22(1):85-95. doi: 10.1007/s12311-021-01365-1. Epub 2022 Feb 4.

Abstract

This cohort study aims to evaluate the predictive validity of multimodal clinical assessment and quantitative measures of in- and off-laboratory mobility for fall-risk estimation in patients with cerebellar ataxia (CA).Occurrence, severity, and consequences of falling were prospectively assessed for 6 months in 93 patients with hereditary (N = 36) and sporadic or secondary (N = 57) forms of CA and 63 healthy controls. Participants completed a multimodal clinical and functional fall risk assessment, in-laboratory gait examination, and a 2-week inertial sensor-based daily mobility monitoring. Multivariate logistic regression analyses were performed to evaluate the predictive capacity of all clinical and in- and off-laboratory mobility measures with respect to fall (1) status (non-faller vs. faller), (2) frequency (occasional vs. frequent falls), and (3) severity (benign vs. injurious fall) of patients. 64% of patients experienced one or recurrent falls and 65% of these severe fall-related injuries during prospective assessment. Mobility impairments in patients corresponded to a mild-to-moderate ataxic gait disorder. Patients' fall status and frequency could be reliably predicted (78% and 81% accuracy, respectively), primarily based on their retrospective fall status. Clinical scoring of ataxic symptoms and in- and off-laboratory gait and mobility measures improved classification and provided unique information for the prediction of fall severity (84% accuracy).These results encourage a stepwise approach for fall risk assessment in patients with CA: fall history-taking readily and reliably informs the clinician about patients' general fall risk. Clinical scoring and instrument-based mobility measures provide further in-depth information on the risk of recurrent and injurious falling.

摘要

这项队列研究旨在评估多模式临床评估以及实验室内外活动能力的定量测量对于小脑共济失调(CA)患者跌倒风险估计的预测效度。对93例遗传性(N = 36)和散发性或继发性(N = 57)CA患者以及63名健康对照者进行了为期6个月的前瞻性评估,内容包括跌倒的发生情况、严重程度及后果。参与者完成了多模式临床和功能性跌倒风险评估、实验室步态检查以及为期2周的基于惯性传感器的日常活动监测。进行多变量逻辑回归分析,以评估所有临床及实验室内外活动测量指标对于患者跌倒(1)状态(未跌倒者与跌倒者)、(2)频率(偶尔跌倒与频繁跌倒)和(3)严重程度(良性跌倒与致伤性跌倒)的预测能力。在前瞻性评估期间,64%的患者发生了一次或多次跌倒,其中65%的跌倒导致了严重损伤。患者的活动能力受损表现为轻度至中度共济失调步态障碍。患者的跌倒状态和频率能够得到可靠预测(准确率分别为78%和81%),主要基于他们既往的跌倒状态。共济失调症状的临床评分以及实验室内外步态和活动测量指标改善了分类,并为跌倒严重程度的预测提供了独特信息(准确率84%)。这些结果鼓励采用逐步评估的方法来评估CA患者的跌倒风险:询问跌倒病史能够快速且可靠地让临床医生了解患者的总体跌倒风险。临床评分和基于仪器的活动测量指标可提供关于反复跌倒和致伤性跌倒风险的进一步深入信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40c5/9883327/4d3feefedaa1/12311_2021_1365_Fig1_HTML.jpg

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